Killing in Combat as a Potentially Morally Injurious Event: The Diverging Psychological Impact of Killing on Peacekeepers and Combat-Oriented Troops

Abstract

The impact of killing in combat (KIC) on veterans’ long-term psychological health is multifaceted and influenced by deployment contexts. This study compared two samples of Norwegian veterans from combat-oriented (Afghanistan 2001–2011, N = 4,053) and peacekeeping (Lebanon 1978–1998, N = 10,605) missions to examine how personal threats, witnessing death/injury, and KIC uniquely predicted long-term mental health, alcohol use, and quality of life (QoL). In the combat-oriented sample, personal threats and witnessing death/injury predicted negative outcomes, while KIC did not. Among peacekeepers, personal threats, witnessing death/injury, and KIC independently predicted posttraumatic stress disorder (PTSD), depression, anxiety, alcohol use, insomnia, and lower QoL. These findings reveal diverging effects of KIC on veterans from combat-oriented and peacekeeping missions, respectively, suggesting that the impact of potentially morally injurious events like KIC is shaped by mission-specific contextual factors.

Keywords

killing moral injury combat PTSD trauma violence veterans peacekeeping

For most civilians in the modern era, killing another human is a rare experience (Pinker, 2011; Weiss et al., 2016). However, killing is not uncommon for soldiers deployed to a war zone (Hoge et al., 2004; Maguen et al., 2010). One of the primary tasks of soldiers is to engage, and thereby potentially harm or kill, enemy combatants—acts that per se are considered highly immoral in peacetime civil society. This context-dependent difference in moral expectations for killing and the large number of veterans who have returned from the high-intensity conflicts of the recent era (Morgan et al., 2019) combine to underscore the importance of understanding the implications of killing in combat (KIC) for veteran mental health and wellbeing. Alongside differences between civil society and war zones, military deployment contexts can have different rules of engagement (ROEs) which also carry with them different implications for when KIC is condoned. Perhaps owing to this normative heterogeneity across deployment contexts, several studies have demonstrated an association between KIC and subsequent mental health problems among military veterans (Fontana et al.,1992; Maguen et al., 2009, 2010, 2011; Van Winkle & Safer, 2011), while other research has found contradicting results indicating that killing enemy combatants may potentially buffer against posttraumatic stress disorder (PTSD; Cesur et al., 2013; Shea et al., 2017). These contradictory findings suggest that further theory-driven research attending to the operational contexts in which KIC occurs is needed to more fully understand the psychological impact of such experiences on combat veterans.

KIC as a Contextually Bound Experience: Theoretical Foundations

Even though the psychological impact of taking lives remains understudied within traumatology and clinical psychology (Porter, 2018; Presseau et al., 2019), the issue has been hotly debated in other social sciences. Some scholars argue that the taboos against killing reflect deontological truths about human nature, that is, killing another human is innately an “unnatural” act for most people (i.e., Dyer, 1985; Grossman, 1996). Representing this perspective, the book On Killing by David Grossman (1996) posits that KIC is one of the most significant, dramatic, and potentially traumatic experiences a soldier can have in war (p. 31), claiming that “there is within most men an intense resistance to killing their fellow man” (Grossman, 1996, p. 4). However, this statement is not congruent with the experiences of all soldiers (Bourke, 1999; Bradley, 2009; Engen, 2009; Møller, 2010; Nadelson, 2005; Reichelt Jon, 2016) and has been criticized for being founded on methodologically unsound studies (Chambers, 2003). Offering an alternative view, evolutionary psychologists (Duntley & Buss, 2008; Shaver & Mikulincer, 2011), as well as primatologists and anthropologists (e.g., Wilson & Wrangham, 2003; Wrangham, 1999), argue that rather than being naturally averse to conspecific killing, humans are adapted specifically for lethal violence under certain conditions. This perspective, commonly labeled the Hobbes-Huxley position, argues that conspecific violence in human evolutionary history is frequent and adaptive, positing that inter-subjective structures such as social frameworks, legal and judicial institutions, culture, and shared values hold us back from engaging in frequent violence (Keeley, 1996; Wrangham, 2018). In a similar vein, theories of normative conduct suggest that an individual’s moral standards arise from group norms that are contingent upon the inter-subjective structures they are subject to (e.g., Bear & Knobe, 2017; Heyes, 2024). Accordingly, whether taking a life is perceived as morally problematic or not will, by this framing, largely depend on whether the act of killing aligns with others’ perceptions of right and wrong—something that is, by definition, contextually-bound (e.g., Bear & Knobe, 2017; de Rond & Lok, 2016). In other words, when it comes to KIC, it may be that what is innate is not an aversion to killing per se, but rather an aversion to killing in contexts where to do so would violate the group norms of the society the perpetrator belongs to.

In the context of a military deployment, norms, rules, and guidelines for conduct in combat are heavily influenced by formalized ROEs. In broad terms, distinctions are typically made between self-defense ROEs and mission accomplishment ROEs, as well as between ROEs that are restrictive in nature and those that constitute a more permissive approach to combat (e.g., Cooper, 2014). ROEs will differ depending on factors such as the purpose of the deployment, the intergovernmental organizational affiliation (e.g., North Atlantic Treaty Organization [NATO] or the United Nations [UN]) of the mission, and national guidelines (Cooper, 2019). For the individual soldier on a mission, ROEs are not abstract legalese, rather they shape the normative pressures in their peer group and define right from wrong in many highly challenging and fast-paced ethical considerations (Frost-Nielsen, 2018), for example, whether to kill an armed person running away from you.

KIC as a Potential Morally Injurious Event

In alignment with discussions of killing as aversive vis-à-vis social norms, in the recent years, there has been increasing interest in examining killing and its impact on veteran psychological health through the lens of moral injury (MI; e.g., Burkman et al., 2022; Purcell et al., 2016). MI provides a broader framework for understanding a range of trauma-related psychological responses and their precipitating stressors, not encompassed by traditional conceptions of PTSD (Griffin et al., 2019; Stein et al., 2012). The symptom cluster labeled as MI commonly does not conform with conceptualizations of posttraumatic distress as a primarily anxiety-based syndrome resulting exclusively from experiences of intense fear (Anyan et al., 2024; Jordan et al., 2017; Nordstrand et al., 2019). Rather, MI is usually described as a cluster of guilt- and shame-based responses to “perpetrating, failing to prevent, bearing witness to, or learning about acts that transgress deeply held moral beliefs and expectations” (Litz et al., 2009, p. 695). These types of experiences can be referred to as “potential morally injurious events” (PMIEs; e.g., Jinkerson, 2016). Several studies within MI research have specifically examined KIC (Burkman et al., 2022; Fontana & Rosenheck, 1999; Frankfurt & Frazier, 2017; Maguen et al., 2009, 2013; Rona et al., 2009), and many regard such experiences to be an archetypical PMIE (e.g., Farnsworth et al., 2014; Kline et al., 2016; Maguen et al., 2012). However, the conditions under which KIC constitutes a PMIE remain poorly understood, and the potential negative psychological sequela of taking a life is likely to be heavily influenced by the backdrop of the military action where it occurs (Purcell et al., 2016). Said differently, KIC does not happen in a vacuum, and contextual factors may moderate the impact of KIC (Porter et al., 2018). Accordingly, one would expect soldiers deployed as peacekeepers to have different reactions to KIC when compared to troops deployed in a combat-oriented mission (Porter, 2018). Attending to these differences may help explain the contradictions in the current literature.

Empirical Complexity in Studying KIC

Despite recent advances in our understanding of war-zone trauma exposure (e.g., Anyan et al., 2024), the complexity of war-zone trauma continues to present several notable challenges to studying the phenomenon. Broadly speaking, contradictory empirical findings regarding KIC may be partially attributed to inherent challenges associated with studying the links between specific stressor exposure and posttraumatic outcomes in military populations (Able & Benedek, 2019; Tanielian et al., 2008). Civilian trauma cohorts often comprise individuals who have experienced singular, horrific events, such as manmade or natural disasters, acts of violence or sexual assault (Atwoli et al., 2015; Gradus, 2017), or trauma occurring within close relationships, such as child maltreatment or domestic abuse (e.g., Copeland et al., 2018; Hughes et al., 2017). In contrast, military personnel deploying to a war zone usually reside there for a prolonged period, often being exposed to the suffering of civilians, and in combat, they may both experience and perpetrate violence (Pietrzak et al., 2011; Yehuda et al., 2015).

Given this war-zone-specific complexity, it is key to concurrently consider the effects of a range of war zone stressors when investigating the unique psychological impact of killing on the battlefield (Kline et al., 2016). In general, killing in a military context often co-occurs with intense combat exposure and life threats due to being in close contact with the enemy (Figley & Nash, 2007). The links between experiences of personal threat and psychological distress are well established (Ben-Zur & Zeidner, 2009; Iversen et al., 2008; James et al., 2013; Ozer et al., 2003) and highlight the importance of examining self-perceived threats when trying to identify the unique influences of various war-zone exposures such as KIC (Cesur et al., 2013; King et al., 1995).

While important, experiencing personal threats does not fully account for the psychological impact of operating in a war zone. In such environments, soldiers also routinely witness the suffering and death of both the local civilian population and other injured soldiers (Fontana & Rosenheck, 1999; Tanielian et al., 2008). Research has indicated that sensory impressions of death, injuries, or the suffering inflicted upon others may cause psychological distress in exposed troops, beyond what can be explained by any associated personal threat (Green et al., 1990; Nordstrand et al., 2019; Pietrzak et al., 2011; Ramage et al., 2015; Shea et al., 2017; Vermetten & Jetly, 2018). Taken together, this implies that the psychological impact of KIC on soldiers needs to be examined with close attention to concurrent trauma exposure (e.g., controlling for experiencing personal threats and witnessing death/injury in others).

Current Study

The current study aimed to investigate veterans from two distinct deployment contexts—peacekeeping and combat missions—to address contextual and trauma-related factors that prior research has identified as critical for long-term mental health outcomes after KIC. Specifically, this study examined the relationship between exposure to different war-zone stressors—KIC, experiencing personal threats, and witnessing suffering and death—and various post-deployment outcomes, including psychological distress (PTSD symptoms, depression, anxiety, insomnia), alcohol use, and poor quality of life (QoL).

To guide our analysis, we addressed the following research question: How does the war zone stressors KIC, personal threats, and traumatic witnessing affect soldiers across deployment contexts with qualitatively different operational parameters?

We hypothesized the following:

Hypothesis 1 (H1): After controlling for exposure to other war-zone stressors, KIC would have stronger associations with psychological distress, alcohol use, and QoL among soldiers deployed to UN peacekeeping missions in Lebanon than among soldiers deployed to more combat-oriented missions in Afghanistan.

Hypothesis 2 (H2): For both combat-oriented and peacekeeping veterans, experiences of personal threats and witnessing atrocities and suffering would significantly influence reported psychological distress, alcohol use, and perceived QoL.

This framework allows for direct comparison of the psychological impact of KIC between deployment contexts, providing insights into how operational differences, such as ROEs, shape post-deployment mental health outcomes.

Methods

Transparency and Openness Statement

The study materials and syntax used to create the results are available at https://osf.io/8abew/?view_only=a66d7cf8c4b54538b04ba2ba2d30b1b6.

Participants and Procedures

Analyses were carried out in two discrete samples of Norwegian veterans. Study 1 consisted of veterans from the recent era NATO missions in Afghanistan. Study 2 consisted of veterans who had been deployed as UN peacekeepers to Lebanon.

Study 1: Veterans From NATO-Led Combat-Oriented Missions in Afghanistan

In Study 1, researchers drew upon data from a cross-sectional survey conducted in the spring of 2012, focusing on Norwegian military personnel deployed to Afghanistan between December 2001 and December 2011. Invitations to participate were sent to all identified personnel. Participants were given the option to complete either a paper version of the questionnaire or an equivalent digital version, both provided via mail alongside a letter containing an internet link and unique login details. As an incentive, participants were entered into a lottery to win one of three sports watches upon completing the survey.

The data-collection process spanned 13 weeks, from February 20 to May 24, 2012, with two follow-up reminders sent to non-responders. The initial reminder was delivered through the postal service, while the second was distributed through both mail and SMS. Out of 7,155 invited personnel, 4,225 individuals (59.0%) responded. However, 172 of these responses (4.1%) were either incomplete or explicit refusals to participate. In total, 3,102 individuals (43.3%) did not provide usable data, including non-responders and those with incomplete submissions. A final sample of 4,053 fully-completed questionnaires were achieved, corresponding to a response rate of 56.7%. Among these valid respondents, 91.7% were recorded as biological males, and 8.3% as biological females in the military health registry. On average, participants were surveyed 5.15 years after their deployment (SD = 2.46, range = 1–10 years).

Study 2: Veterans From UN-Led Peacekeeping Missions in Lebanon

In Study 2, a dataset was drawn from a cross-sectional, post-deployment survey targeting Norwegian peacekeepers who had served with the UN Interim Force in Lebanon (UNIFIL). This survey was carried out between September 2014 and April 2015. Invitations to participate were extended to all Norwegian military personnel deployed to Lebanon between 1978 and 1998, totaling 20,678 individuals, both men and women. Participants were provided with a printed version of the questionnaire and a letter containing a web link and unique login credentials, enabling them to choose between completing the paper form or a corresponding digital version. Follow-up reminders were sent twice: the first by mail and the second by both mail and SMS.

A total of 11,633 individuals responded to the survey. However, 1,028 responses were excluded due to active refusals (n = 913) or incomplete submissions (n = 115). This left 10,605 valid responses, resulting in a final positive response rate of 51.3%. Among these valid responses, 97.1% were identified as biological males, and 2.9% as biological females, according to the military health registry. On average, participants were surveyed 28.36 years after their deployment (SD = 5.96, range = 18–38 years).

The Operational Context and Mission Statements of the Two Samples

The Norwegian military contribution in Lebanon was as part of a UN-mandated peacekeeping mission, and the main objective was not to engage and defeat an enemy but to maintain order, act as a stabilizing force, and observe and report transgressions of the peace accord (Sareen et al., 2007). Troops had extensive contact with the local population and were encouraged to develop positive relationships with the local civilian population (Weiseth & Dittmann, 1997). Moreover, there were restrictive ROEs for combat that emphasized the use of deadly force as a last resort, only to be used for self-defense (Weiseth & Dittmann, 1997). Even protecting the local civilians from deadly assault was not necessarily permitted within the ROEs.

In contrast, the NATO-led military engagement in Afghanistan mostly consisted of combat-oriented missions (e.g., Cooper, 2019; Yost, 2007). The Norwegian engagement in Afghanistan was established because the United States invoked Article 5 of the NATO treaty following the terrorist attacks on September 11, 2001. Troops were deployed with permissive ROEs (Cooper, 2019), as well as stated aims of defeating the enemy (e.g., the Taliban, Al Qaeda, and the ISIS-K) through military means (e.g., Berenguer López, 2024; Hilde, 2024). Empirical studies of Scandinavian Afghanistan veterans suggest that these soldiers generally sought to develop a realistic understanding of what deployment to Afghanistan would entail, also counting combat situations and the harsh operational demands of being a warfighter (Lien et al., 2016; Møller, 2010; Waaler et al., 2019).

Ethical Considerations

All survey data from both studies were retrieved from the Norwegian Armed Forces Health Registry. Researchers had access only to de-identified data, ensuring participant confidentiality. Written informed consent was obtained from all participants. The procedures for data collection, storage, and distribution complied with the legal regulations governing the Norwegian Armed Forces Health Registry. The study followed Norwegian health research laws and adhered to the ethical principles outlined in the Helsinki Declaration. It was approved by the Regional Committee for Medical and Health Research Ethics (REK) of South-East Norway (case number: 33032).

In addition, REK approved the anonymous collection of health-related information about non-responders to the survey invitations. This comparison involved analyzing demographic data sourced from the Norwegian Armed Forces Health Registry, along with information on sick leave and benefit usage obtained from the Norwegian Labor and Welfare Administration (Arbeids- og velferdsforvaltningen, NAV).

Measures

Demographic Variables and Time Since Deployment

The demographic variables of age, level of education, and cohabitation have all been found to influence levels of psychological distress, QoL, and substance use after exposure to major stressors (Iversen et al., 2008; James et al., 2013; Riddle et al., 2007; Schnurr et al., 2004). Accordingly, these variables were used as covariates in the regression analysis (see Tables 1 and 3 for M and SD). In Study 1 (Veterans from a Combat Mission), age was assessed using an open-ended integer response, whereas respondents in Study 2 indicated their age using a set of fixed-interval categories (0 = 20–29; 1 = 30–39; 2 = 40–49; 3 = 50–59; 4 = 60–69; 5 = 70+). In both studies, education was measured using an ordinal scale (0 = primary schooling; 1 = upper secondary schooling; 2 = lower degree; 3 = graduate degree), and respondents living with a partner (both those married and unmarried) were categorized as cohabitating in the dummy-coded predictor (cohabitate = 1). To control for the possible effects of the time since trauma, length of time (in years) since the last deployment prior to the participation in the surveys was used as a covariate. While this variable does not accurately measure the time since experiencing war-zone stressors, it provides an approximation of the time elapsed since likely exposure.

Killing in Combat

We identified separate KIC variables for the two studies (see Tables 1 and 3 for M and SD). Study 1 (Veterans from a Combat Mission) had two items related to KIC, that is, “I took lives in combat” and “I think I took lives in combat,” both with the response options 0 (no); 1 (1–2 times); 2 (3–12 times); 3 (13–50 times); and 4 (50 times or more). The two items were merged to create a single variable that was used to indicate having killed while deployed in Afghanistan. Study 2 (Veterans from a Peacekeeping Mission) had a single item that captured KIC events: “I took a life/lives while I was deployed to Lebanon,” with the response options 1 (no); 2 (yes, 1–2 times); 3 (yes, 3–5 times); and 4 (yes, more than 5 times). This item was used to indicate anyone who had killed during their deployment to Lebanon. The KIC variables in both studies were converted into dummy variables for further analysis, with the nominal values: not killed (0) and killed (1).

War-Zone Stressors

The research teams of both Study 1 and 2 developed distinct war-zone stressor indices for their respective surveys; however, there was substantial overlap. The events described in both the indices covered a range of previously described aversive war-zone stressors common to military deployment (Fontana et al., 1992; King et al., 1995; Litz et al., 2009; Maguen et al., 2010; Nash & Figley, 2007; Pietrzak et al., 2011; Stein et al., 2012). At the outset, the war-zone indices of the Study 1 (Afghanistan, combat-oriented sample) survey and the Study 2 (Lebanon, peacekeeper sample) survey consisted of 23 and 39 items, respectively. There were some differences in the wording of described events in the two surveys, idiomatic to the respective mission areas. Both indices were self-report scales and measured the frequency of exposure to different types of war-zone stressors, such as hazardous environments, threats to life or physical harm, as well as witnessing death and injury in others. In both studies, the items were rated on a 5-point scale. In Study 1 (Veterans from a Combat Mission), the response options were 0 (not experienced); 1 (experienced 1–2 times); 2 (experienced 3–12 times); 3 (experienced 13–50 times); and 4 (experienced 50 times or more), giving a total score range of 0 to 92, with higher scores indicating exposure to more stressors. In Study 2 (Veterans from a Peacekeeping Mission), the response options were 1 (no); 2 (yes, 1–2 times); 3 (yes, 3–5 times); and 4 (yes, more than 5 times), giving a total score range of 39–156, with higher scores indicating exposure to more stressors.

Based on a targeted review of relevant papers focused on war zone trauma (Fontana & Rosenheck, 1999; Green et al., 1990; Iversen et al., 2008; Jordan et al., 2017; Maguen et al., 2013; Ozer et al., 2003; Pietrzak et al., 2011; Ramage et al., 2015; Riddle et al., 2007; Shea et al., 2017), we constructed a personal threats and a traumatic witnessing variable for both studies. The Personal Threats variables in Study 1 (α = .69) and Study 2 (α = .65) consisted of four and six items, respectively. The traumatic witnessing variables consisted of five items in Study 1 (α = .64), and five items in Study 2 (α = .67). The personal threats items in both studies consisted of questions related to experiences of being in physical danger, for example, “I experienced a moment I thought I would die” and “I was attacked by the enemy.” The traumatic witnessing items in both studies related to exposure to other people’s suffering or death, for example, “I handled dead bodies or body-parts” and “I witnessed innocent victims of war.” The stressor variables were not mutually exclusive; we assumed that some events could involve multiple stressor types.

Posttraumatic Stress Symptoms

The Posttraumatic Stress Disorder Checklist-17, military version (PCL-M; Weathers et al., 1993) was used to capture posttraumatic stress (PTS) symptoms in both Study 1 (α = .89) and Study 2 (α = .95). The self-report scale contains 17 items indexing symptoms of PTSD (Blanchard et al., 1996). Each item is rated on a 5-point Likert-type scale (1: not at all to 5: extremely). The total possible score range is 17–85, with a higher score indicative of more symptoms.

Anxiety and Depression

The Hospital Anxiety and Depression Scale (HADS) is a widely recognized tool for assessing symptoms of anxiety and depression (Zigmond & Snaith, 1983). It comprises 14 items divided into two subscales: Anxiety (HADS-A; seven items) and Depression (HADS-D; seven items). Each item is scored on a 4-point scale ranging from 0 to 3, resulting in a total score range of 0–42, and a subscale range of 0–21. Higher scores reflect greater symptom severity.

In both studies, HADS-A and HADS-D were employed to assess levels of anxiety (Study 1: α = .77; Study 2: α = .88) and depression (Study 1: α = .78; Study 2: α = .84).

Insomnia

The Insomnia Severity Index (ISI; Bastien et al., 2001) is a seven-item self-report measure designed to assess the severity of insomnia symptoms. This scale was utilized in both studies to evaluate participants’ experiences of insomnia, with reliability coefficients indicating strong internal consistency (Study 1: α = .89; Study 2: α = .93). Each of the seven items is rated on a 5-point scale ranging from 0 to 4, resulting in a total possible score between 0 and 28. Higher total scores correspond to more severe insomnia symptoms. The ISI captures various aspects of insomnia, including difficulties with falling asleep, staying asleep, and early morning awakenings, as well as the impact of these difficulties on daily functioning and overall QoL.

Alcohol Use

The Alcohol Use Disorder Identification Test (AUDIT; Babor et al., 2001) is a widely utilized 10-item questionnaire designed to detect problematic patterns of alcohol consumption. Eight items assessing current alcohol use are scored on a 5-point scale from 0 to 4, while two items are scored with values of 0, 2, or 4. This results in a total score range of 0 to 40, with higher scores reflecting greater levels of alcohol use. The AUDIT demonstrated acceptable reliability in both studies (Study 1: α = .71; Study 2: α = .82).

Quality of Life

The Satisfaction with Life Scale (SWLS; Diener et al., 1985) is a five-item, self-report measure indicating perceived QoL. Each item is rated on a 5-point scale that ranges from 1 (completely disagree) to 5 (completely agree). Only the first four items of the SWLS were available, both in Study 1 and Study 2. In addition, a single item commonly used to indicate QoL in Norwegian general health surveys (e.g., Stordal et al., 2003) was added in both studies: “When you think about how you are feeling these days, are you mostly satisfied with your existence or are you mostly unhappy with your existence?” This added item was rated from 1 (very dissatisfied) to 7 (very satisfied). Grouped as a single variable, the possible score ranged from 5 to 27 and indicated QoL in both studies (Study 1: α = .85; Study 2: α = .88). A higher score represented higher levels of perceived QoL.

Analysis Strategy

A multiple regression analysis was conducted by specifying a path analysis model using Mplus 8.8 (Muthén & Muthén, 1998–2018) with PTSD depression, anxiety, and alcohol use disorder (AUD) symptoms, as well as insomnia and QoL as dependent variables, and age, education, cohabitation status, time since deployment, personal threat, traumatic witnessing, and KIC as predictors. The small amount of missing data (<3.4%) was handled through the multiple imputation module provided by Mplus using 2 Markov Chain Monte Carlo (MCMC) chains to generate 50 imputed datasets with 10% thinning. The imputed datasets were estimated using robust maximum likelihood estimation to account for violations of the multivariate normality assumption.

Results

Descriptive Statistics

Correlations, means, and standard deviation for the primary study variables based on imputed values are provided in Table 1. Values for the combat-oriented sample (Study 1) are provided above the diagonal, and values for the peacekeeper sample (Study 2) are provided below. The majority of correlations between the primary predictors (personal threat, traumatic witnessing, KIC) and outcome (PTSD symptoms, depression, anxiety, insomnia, AUD symptoms, QoL) variables were statistically significant in the expected direction and were generally consistent across studies. Given its role as a focal predictor, rates of KIC were compared across the two studies. As expected, a chi-square independence test revealed that the observed rates of KIC were significantly higher in Study 1 (13.14%) relative to Study 2 (1.47%), χ² (1) = 870.66, p < .01, φ = .25.

Table 1.

Correlations, Means, Standard Deviations, and Missingness Rates for Primary Study Variables.

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	Mean	SD	%Miss
1. PTSD Sx	—	.701	.692	.497	.247	−.439	−.098	−.108	−.074	.007	.213	.241	.135	1.233	0.358	1.600
2. Depression Sx	.742	—	.601	.412	.164	−.522	−.048	−.056	−.077	.019	.097	.139	.069	0.253	0.346	1.500
3. Anxiety Sx	.780	.751	—	.470	.253	−.398	−.126	−.054	−.039	.026	.107	.147	.053	0.418	0.397	1.400
4. Insomnia	.667	.597	.665	—	.166	−.339	.037	−.052	−.084	−.009	.045	.095	.013	0.518	0.480	2.000
5. AUD Sx	.290	.247	.297	.291	—	−.166	−.296	−.176	−.209	−.054	.178	.068	.117	5.949	3.339	1.700
6. Quality of life	−.582	−.657	−.595	−.515	−.223	—	.006	.109	.239	.064	−.027	−.060	−.005	3.944	0.735	1.700
7. Age	.000	−.023	−.082	.001	−.064	.058	—	.231	.158	−.079	−.262	−.054	−.192	30.203	9.234	0.000
8. Education	−.110	−.084	−.055	−.076	−.042	.110	−.065	—	.103	.091	.196	.003	.146	2.092	0.964	0.500
9. Cohabitation status	−.148	−.169	−.122	−.123	−.095	.294	−.045	.067	—	.141	−.108	−.011	−.066	0.719	0.449	1.500
10. Time since deployment	.064	.023	.003	.047	.028	.000	.589	−.123	−.034	—	−.079	.073	−.059	5.144	2.460	0.400
11. Personal threat	.284	.186	.235	.207	.096	−.140	.012	−.055	−.011	.090	—	.399	.654	0.331	0.469	1.600
12. Witnessing	.231	.143	.190	.171	.085	−.104	−.013	.050	.005	.013	.323	—	.230	0.506	0.516	1.600
13. Killing in combat	.160	.092	.098	.087	.057	−.069	.041	−.027	−.022	.090	.109	.085	—	0.132	0.338	2.700
M	1.370	0.352	0.503	0.810	5.380	3.957	1.994	1.426	0.769	10.368	0.513	0.526	0.015
SD	0.636	0.480	0.546	0.837	4.300	0.896	0.860	0.769	0.422	5.950	0.500	0.499	0.122
% Miss	1.100	0.900	0.900	0.900	1.100	0.900	0.600	0.400	3.400	0.500	0.900	0.900	1.000

Note. PTSD = posttraumatic stress disorder; Sx = symptoms; AUD = alcohol use disorder. Study 1 (Lebanon) peacekeepers sample (N = 10,481) statistics provided below the diagonal. Study 2 (Afghanistan) combat-oriented sample (N = 4,027) statistics provided above the diagonal. Lower diagonal values greater than .020, and upper diagonal values greater than .031 are significant at the p < .05 level.

Comparison of Responders and Non-Responder

Study 1

To validate the representativeness of the responders in the sample, the Norwegian Armed Forces Joint Medical Services (NAFJMS) conducted a non-responder analysis of those veterans who did not participate in the Afghanistan 2012 study. The non-responders (n = 3,102) were compared with the responders (N = 4,053) using Pearson’s chi-square tests of independence. The attrition analysis found non-responders had more long-term sick leave and social benefits than the survey responders (p < .001). Accordingly, there was a response bias in terms of study participants being in better health and having less need of government assistance than the non-responders. Moreover, there were significant differences in biological sex and age between responders and non-responders (p < .001) such that women and older veterans had higher response rates.

Study 2

To determine the generalizability of the study sample to the entire Lebanon veteran cohort, a non-responder analysis was conducted. Using Pearson’s chi-square tests of independence, the responder group and the non-responder group were compared on the following variables: biological sex, age, short-term sick leave, long-term sick leave, long-term welfare benefits, and sick leave due to mental illness. The responders were significantly older and had significantly lower frequencies of short- and long-term sick leaves, long-term welfare benefits, and sick leave due to mental illness (p < .001). Thus, similar to the trend in the combat-oriented sample, these results show a response bias in terms of responders being in better health and having less need of government assistance than the non-responders. Unlike in the combat-oriented sample, there was, however, no significant difference between responders and non-responders regarding biological sex.

Regression Analyses

Model results for PTSD, depression, and anxiety symptoms are provided in Table 2. The coefficients for insomnia, AUD symptoms, and perceived QoL are in Table 3.

Table 2

Multiple Regression Results for Post-Traumatic Stress Disorder, Depression, and Anxiety Symptoms.

Outcome	Predictor	Study 1: Combat-oriented sample				Study 2: Peacekeepers sample
Outcome	Predictor	Est	[95% CI]	Est/SE	β	Est.	[95% CI]	Est/SE	β
	Age	−.001	[−.002, .000]	−2.055*	−.033	−.030	[−.045, −.016]	−4.097**	−.041
	Education	−.028	[−.040, −.016]	−4.563**	−.075	−.076	[−.090, −.061]	−10.175**	−.091
Post-traumatic stress disorder symptoms	Cohabitation	−.039	[−.066, −.012]	−2.840**	−.049	−.209	[–.241, –.178]	−13.031**	−.139
	Time deploy	.002	[−.003, .006]	0.782	.012	.004	[.002, .007]	3.535**	.041
	Personal threat	.082	[.046, .119]	4.379**	.108	.269	[.247, .291]	23.873**	.211
	Witnessing	.135	[.107, .164]	10.257**	.195	.200	[.178, .222]	17.777**	.157
	Killing	.000	[−.048, .049]	0.018	.000	.607	[.429, .842]	6.670**	.116
	R²	.085	—	—	—	.148	—	—	—
	Age	.000	[−.002, .001]	−0.559	−.010	−.027	[−.039, −.015]	−4.528**	−.049
	Education	−.015	[−.027, −.004]	−2.563*	−.042	−.043	[−.055, −.032]	−7.547**	−.070
	Cohabitation	−.054	[−.080, −.027]	−4.031**	−.070	−.186	[–.211, –.162]	−14.931**	−.164
Depression symptoms	Time deploy	.004	[−.001, .008]	1.632	.026	.001	[.000, .003]	1.484	.018
Depression symptoms	Personal threat	.016	[−.018, .050]	0.931	.022	.136	[.118, .154]	14.697**	.142
	Witnessing	.083	[.056, .110]	6.143**	.123	.091	[.073, .110]	9.904**	.095
	Killing	.016	[−.030, .061]	0.678	.015	.248	[.134, .363]	4.244**	.063
	R²	.029	—	—	—	.081	—	—	—
	Age	−.004	[−.006, −.003]	−6.267**	−.104	−.074	[−.087, −.061]	−11.185**	−.116
	Education	−.010	[−.024, .003]	−1.512	−.025	−.031	[−.044, −.018]	−4.725**	−.044
	Cohabitation	−.016	[−.045, .013]	−1.081	−.018	−.155	[–.182, –.129]	−11.493**	−.120
Anxiety symptoms	Time deploy	.002	[−.003, .007]	0.917	.014	.003	[.001, .006]	3.224**	.037
Anxiety symptoms	Personal threat	.033	[−.006, .072]	1.669	.039	.198	[.178, .219]	18.939**	.181
	Witnessing	.101	[.072, .129]	7.070**	.131	.138	[.118, .159]	13.252**	.126
	Killing	−.031	[−.081, .019]	−1.207	−.026	.291	[.166, .417]	4.555**	.065
	R²	.038	—	—	—	.100	—	—	—

Note. Significant focal predictors denoted by bold formatting. CI = confidence interval.

p < .05. **p < .01.

Table 3.

Multiple Regression Results for Sleep Disturbance, Alcohol Use Disorder Symptoms, and Quality of Life.

Outcome	Predictor	Study 1: Combat-oriented				Study 2: Peacekeepers
Outcome	Predictor	Est	[95% CI]	Est/SE	β	Est.	[95% CI]	Est/SE	β
	Age	.004	[.002, .006]	4.046**	.072	−.029	[−.050, −.008]	−2.733**	−.030
	Education	−.029	[−.045, −.013]	−3.558**	−.059	−.067	[−.087, −.047]	−6.614**	−.062
	Cohabitation	−.095	[–.130, −.060]	−5.341**	−.089	−.232	[–.272, –.193]	−11.418**	−.117
Insomnia	Time deploy	.002	[−.005, .008]	0.513	.008	.004	[.001, .008]	2.713**	.032
Insomnia	Personal threat	.021	[−.025, .066]	0.898	.020	.260	[.228, .293]	15.658**	.155
	Witnessing	.087	[.053, .122]	5.037**	.094	.199	[.167, .231]	12.020**	.119
	Killing	−.031	[−.089, .027]	−1.048	−.022	.373	[.194, .552]	4.079**	.054
	R²	.023	—	—	—	.078	—	—	—
	Age	−.085	[−.096, −.074]	−14.830**	−.236	−.605	[–.710, –.500]	−11.297**	−.121
	Education	−.310	[–.420, –.200]	−5.621**	−.089	−.178	[–.287, −.069]	−3.210**	−.032
Alcohol use disorder symptoms	Cohabitation	−1.111	[–1.349, –.874]	−9.312**	−.150	−.963	[–1.201, –.726]	−7.947**	−.094
	Time deploy	−.055	[−.094, −.015]	−2.698**	−.040	.060	[.043, .076]	7.008**	.082
	Personal threat	.530	[.226, .834]	3.417**	.074	.546	[.377, .716]	6.321**	.064
	Witnessing	.187	[−.034, .408]	1.670	.029	.520	[.351, .688]	6.035**	.060
	Killing	−.092	[–.487, .303]	−0.456	−.009	1.401	[.272, 2.530]	2.432*	.040
	R²	.133	—	—	—		—
	Age	−.004	[−.006, −.001]	−2.819**	−.046	.093	[.069, .115]	7.989**	.088
	Education	.077	[.052, .101]	6.185**	.101	.106	[.085, .127]	9.887**	.091
	Cohabitation	.386	[.331, .441]	14.315**	.236	.615	[.572, .658]	27.830**	.289
Quality of life	Time deploy	.008	[−.001, .017]	1.712	.027	−.002	[−.006, .001]	−1.390	−.016
Quality of life	Personal threat	−.014	[−.025, .111]	1.250	.028	–.185	[–.219, –.151]	–10.665**	–.103
	Witnessing	−.151	[–.159, −.059]	−4.280	−.076	–.127	[–.161, −.094]	–7.388**	−.071
	Killing	−.037	[−.051, .127]	0.835	.018	–.334	[–.503, –.165]	–3.868**	−.045
	R²	.073	—	—	—	.125	—

Note. Significant focal predictors denoted by bold formatting. CI = confidence interval.

p < .05. **p < .01.

PTSD Symptoms

Significant covariate effects for age, education, and cohabitation were observed in both the combat-oriented and peacekeepers samples, such that individuals who were older, more educated, and were cohabitating reported lower levels of PTSD symptoms. Respondents in the peacekeeper sample with a longer time since deployment reported higher levels of PTSD symptoms, but this effect did not replicate in the combat-oriented sample. Turning to the focal predictors, significant effects emerged for personal threat (b_Afg = .082 [.046, .119], β_Afg = .108; b_Leb = .269 [.247, .291], β_Leb = .211) and traumatic witnessing (b_Afg = .135 [.107, .164], β_Afg = .195; b_Leb = .200 [.178, .222], β_Leb = .157) in both samples, such that respondents who endorsed these experiences reported higher levels of post-deployment PTSD symptoms. In addition, the experience of KIC was associated with significantly higher levels of PTSD symptoms among respondents in the peacekeeper sample (b_Leb = .607 [.429, .842], β_Leb = .116), but not in the combat-oriented sample.

Depressive Symptoms

Covariate effects emerged for education and cohabitation across both samples, as well as an effect for age among the peacekeeping respondents, such that more educated, cohabitating, and older individuals reported lower levels of depression. A significant effect for traumatic witnessing emerged in both samples (b_Afg = .083 [.056, .110], β_Afg = .123; b_Leb = .091 [.073, .110], β_Leb = .095), with endorsement of this experience associated with higher levels of depression. In addition, endorsement of personal threat (b_Leb = .136 [.118, .154], β_Leb = .142) and KIC (b_Leb = .248 [.134, .363], β_Leb = .063) was uniquely associated with increased levels of post-deployment depression symptoms among respondents in the peacekeepers sample.

Anxiety Symptoms

The covariate effect of “age” in both samples indicated that older respondents reported lower anxiety symptoms, and the significant coefficients for education, cohabitation, and time since deployment in the peacekeeper sample suggest that more educated and cohabitating individuals reported lower levels of anxiety, whereas those with a greater time since deployment reported higher anxiety. Endorsement of traumatic witnessing was associated with higher levels of anxiety in both samples (b_Afg = .101 [.072, .129], β_Afg = .131; b_Leb = .138 [.118, .159], β_Leb = .126), whereas personal threat (b_Leb = .198 [.178, .219], β_Leb = .181) and KIC (b_Leb = .291 [.166, .417], β_Leb = .065) were only associated with higher post-deployment anxiety in the peacekeeper sample.

Insomnia

Older age was associated with greater insomnia in the combat-oriented sample but fewer sleep disturbances in the peacekeeper sample. Significant effects of education and cohabitation were observed in both samples, suggesting that more educated and cohabitating individuals reported lower levels of insomnia. In addition, greater time since deployment was associated with higher levels of insomnia among the peacekeeping respondents. Endorsement of traumatic witnessing was associated with higher levels of insomnia in both samples (b_Afg = .087 [.053, .122], β_Afg = .094; b_Leb = .199 [.167, .231], β_Leb = .119), and endorsement of personal threat (b_Leb = .260 [.228, .293], β_Leb = .155) and KIC (b_Leb = .373 [.194, .552], β_Leb = .054) was uniquely related to post-deployment insomnia among individuals in the peacekeeper sample.

Alcohol Use

Older, more educated, and cohabitating respondents in both samples reported less alcohol use. While a longer time since deployment was associated with less alcohol use in the combat-oriented sample, it was associated with more alcohol use in the peacekeeper sample. In addition, endorsement of personal threat was predictive of more alcohol use in both samples (b_Afg = .530 [.226, .834], β_Afg = .074; b_Leb = .546 [.377, .716], β_Leb = .064), whereas endorsement of traumatic witnessing (b_Leb = .520 [.194, .552], β_Leb = .054) and KIC (b_Leb = 1.401 [.272, 2.530], β_Leb = .040) was only related to more alcohol use in the peacekeeper sample.

Quality of Life

Age was inversely related to QoL in the combat-oriented sample but positively related to QoL in the peacekeeper sample. In both samples, more educated and cohabitating respondents reported higher QoL. Although none of the focal predictors emerged as significantly related to QoL in the combat-oriented sample, endorsement of personal threat (b_Leb = –.185 [–.219, –.151], β_Leb = –.103), traumatic witnessing (b_Leb = –.127 [–.161, −.094], β_Leb = −.071), and KIC (b_Leb = –.334 [–.503, –.165], β_Leb = −.045) were all uniquely associated with lower post-deployment QoL in the peacekeeper sample.

Discussion

The present work examined the unique predictive utility of experiencing personal threats, witnessing death or injury, and KIC, in explaining differences in post-deployment mental health, alcohol use, and QoL indicators. Independent samples of soldiers deployed on combat missions (Study 1, Afghanistan, combat-oriented sample) and soldiers deployed to a peacekeeping mission (Study 2, Lebanon, peacekeeper sample) allowed for an evaluation of how the relationships between personal threat, traumatic witnessing, KIC, and the health and QoL outcomes differ across operational contexts with discrete objectives regarding combat actions. Consistent with both our hypotheses, the results revealed the importance of contextual factors in determining the impact of KIC, while also highlighting the broader psychological risks associated with experiences of personal threats and traumatic witnessing. KIC was significantly associated with all measured outcomes in the peacekeeper sample, including higher levels of PTSD symptoms, depression, anxiety, insomnia, and alcohol use, as well as lower perceived QoL. In contrast, KIC was not significantly related to any outcome variables in the combat-oriented sample. The results also show how experiences of personal threats and witnessing suffering and death during deployment were predictive of negative outcomes across both samples. In the combat-oriented sample, traumatic witnessing emerged as the most consistent predictor of negative outcomes (4 of 6 outcomes), followed by personal threat (2 of 6 outcomes). Among peacekeepers, both personal threats and traumatic witnessing were uniformly predictive of higher levels of PTSD symptoms, depression, anxiety, and insomnia, as well as lower QoL.

The current findings underscore the contextual nature of KIC’s psychological impact, with, in terms of adverse effects, peacekeepers appearing more vulnerable to taking lives than combat soldiers operating under ROEs explicitly geared toward combat. Accordingly, the results challenge prior claims suggesting that KIC persistently precipitate psychological distress among veterans (Farnsworth et al., 2014; Grossman, 1996; Kelley et al., 2019; Maguen et al., 2009, 2010, 2013; Pitts et al., 2014; Van Winkle & Safer, 2011). Consequently, assumptions about the psychological impact of KIC should be tempered, as the findings do not support taking lives in combat as ipso facto damaging to the mental health of the perpetrator.

KIC as a PMIE

Human conspecific killing is a subject where many people have strong moral intuitions due to the societal norms in Western democracies regarding acts of violence (Farnsworth et al., 2014). The topic of MI and the definitions of PMIEs are developing research fields, where the advancement of psychological theory often intersects with contemporary assumptions about human nature prior to thorough empirical investigation. Accordingly, some central assumptions, such as defining KIC generically as a transgressive act that violates one’s values, and thus as a PMIE, may be premature (Frankfurt & Frazier, 2017). Indiscriminately defining something as a transgressive act can confound a potential stressor with the outcome, for example, equating exposure to an incident with the effects of this exposure. Several researchers have recommended emphasizing mediating factors, such as relevant group norm violations, as well as feelings of guilt and shame instead of the external stressors, when defining PMIEs (Button et al., 2017; Farnsworth et al., 2014; Jinkerson, 2016;). The current findings seem to support this position and demonstrate how accounting for contextual factors and relevant group norms may be particularly important for understanding when KIC may constitute a PMIE.

Influence of Mission Objectives on the Psychological Impact of KIC

As hypothesized, the current findings indicate that the operational backdrop of KIC has a significant influence on the long-term mental health consequences of such experiences. In the combat-oriented sample who served in Afghanistan, there was a relatively high proportion of respondents who reported KIC, as opposed to in the peacekeepers sample, where the reported rates of KIC were rather low. This was expected and reflects the very different kinds of mission statements of these two military engagements. It is likely that these fundamental differences in the missions affected both the peritraumatic perceptions of KIC and posttraumatic evaluations of such acts. KIC can be perceived as both illegitimate and legitimate depending on context and the ROEs of a specific mission set. In particular, restrictive or unclear ROEs have been proposed as a major cause for cognitive dissonance after taking lives in combat (Currier et al., 2015; Jinkerson, 2016; Litz et al., 2009; Shay, 2014). Conversely, considered ROEs may protect soldiers against the negative impact of KIC by clearly legitimatizing a set of parameters for such actions, and thus relieve them of a more privatized emotional burden when it happens (French, 2005; Moldjord & Holen, 2005; Rivera et al., 2022). Accordingly, the restrictive ROEs and the peacekeeping mission statement in the Lebanon engagement likely contribute to the negative impact of KIC among peacekeepers veterans in the current study. Consistent with this, investigations into the experiences of peacekeeping forces in general (Sareen et al., 2007; Shigemura et al., 2016), and of Scandinavian peacekeepers in Lebanon in particular (Wallenius, 1997; Wallenius et al., 2004; Weiseth & Dittmann, 1997), have revealed feelings of reluctance during the combat actions, as well as an uncertainty regarding the legitimacy of KIC (Moldjord & Holen, 2005). In contrast, the permissive ROEs and the combat-oriented mission statement of the Afghanistan engagement may help explain the modest post-deployment effects of taking lives among the combat-oriented Afghanistan veterans. This interpretation is also congruent with qualitative reports from Scandinavian Afghanistan veterans who killed in combat while deployed to Afghanistan (Møller, 2010; Waaler et al., 2019).

Altogether, the current findings emphasize the socially embedded nature of PMIEs, as well as how contextual factors play a major role in whether an act is perceived by the individual as morally transgressive. Ultimately, it may be that social and contextual factors largely determine whether a moral stressor leads to psychological distress. The point can be illustrated by studies indicating that it is more common for soldiers to feel post-deployment guilt about their immediate positive reaction to killing an enemy combatant, rather than feeling guilt over the act of killing itself (Kubany et al., 1997; Purcell et al., 2016). Given societal norms in the Western democracies against killing (e.g., Bourke, 1999; Boyd et al., 2003; French, 2005; Henrich et al., 2006; Heyes, 2024; Pinker, 2011), soldiers may anticipate that taking someone’s life should cause distressing feelings, even when it does not. This mechanism may also partially explain the adverse consequences of KIC among the peacekeepers in the current study.

When attempting to adapt to civilian life, a veteran will have to integrate their experience of having killed with the strong societal norms against such actions. This can potentially cause psychological distress and cognitive dissonance (Farnsworth et al., 2014; Kubany et al., 1997). Studies suggest that a negative re-evaluation of war-zone actions when returning home from deployment is particularly dependent on both one’s own and others’ perceptions of the legitimacy of the violence they perpetrated during combat (Kilner, 2000; Nadelson, 2005; Purcell et al., 2016). Again, perceptions of the legitimacy of KIC are highly influenced by the ROEs. As a result, there is a possibility that soldiers in the peacekeepers sample have retrospectively de-emphasized the context of KIC, such as having protected oneself or one’s fellow soldiers (Kelley et al., 2019; Porter, 2018), and end up interpreting themselves as cold-hearted killers (Brown et al., 1999; Janoff-Bulman, 2010). However, clinical interventions that address the contextual predictors of killing as a PMIE can help mitigate these risks (e.g., Darnell et al., 2022). In addition, such interventions can alleviate the dissonance veterans experience when their actions during deployment conflict with societal norms they must navigate in civilian life.

The Role of Context on Personal Threat and Traumatic Witnessing

In the current study, there were differences in how the veterans in the two samples reacted to the two war-zone stressors of personal threats and traumatic witnessing, suggesting that deployment context impacts potentially traumatic events beyond KIC as a PMIE. In the combat-oriented sample, witnessing the death and suffering of others seems to be the most potent war-zone stressor in terms of producing adverse psychological sequelae. In contrast, the pattern in the peacekeepers sample is more in line with traditional expectations concerning traumatic stressors (Ben-Zur & Zeidner, 2009; Ozer et al., 2003), with experiencing personal threats by far accounting for most of the variance in adverse outcomes, while traumatic witnessing also predicted negative developments.

A possible explanation for these findings may be the differences between the combat-oriented troops and the peacekeepers with regards to pre-deployment expectations about what they would encounter on their missions. Norwegian soldiers who deployed to Afghanistan received extensive pre-deployment combat training and mission briefings indicating a high likelihood of being attacked by the enemy during their missions (e.g., Hoiback, 2019; Mogstad et al., 2024). As is typical for military peacekeepers (e.g., Adler et al., 2003), this was not the case for the Norwegian peacekeepers deployed to Lebanon (Weisaeth, 2003; Weiseth & Dittmann, 1997). A recent prospective study on combat veterans who served in Afghanistan demonstrate how positive-expectancy factors (i.e., expectations of an event, valence of the expected event) impact post-deployment mental health after combat exposure (Huffman et al., 2025). Given the likely beneficial levels of positive-expectancy factors regarding combat in the Study 1 cohort, it is not surprising that personal threats were the least-salient trauma type among the combat-oriented soldiers. Similarly, a lack of expectations for traumatic witnessing may have exacerbated negative outcomes for soldiers deployed on combat missions to Afghanistan. Importantly, it is also possible that the observed differences in associations between personal threat, traumatic witnessing, and long-term outcomes be partially attributable to variables not captured by the current study and, thus, warrant further investigation.

Limitations

The current findings should be interpreted considering several study limitations. Of note, there was substantial variation in the length of time since the respondents were exposed to the war-zone stressors when completing the two surveys, particularly in the case of the peacekeeping veterans. Although we controlled for the time since deployment in analyses, length of time may still have affected the accuracy of the retrospective deployment-related reports (McNally, 2005). We also acknowledge that the overall amount of combat occurring in Lebanon and Afghanistan varied significantly across deployments for Norwegian soldiers and, as such, represents an unmeasured contextual variable that could have impacted respondents’ experiences of KIC. Moreover, although operationalizations of the items used to assess KIC and other war-zone trauma exposure differed slightly between studies, the content overlap was high, giving us strong reason to believe these different operationalizations are valid reflections of the same underlying constructs.

The cross-sectional designs of both Study 1 and Study 2 do not capture the changes over time and casual relations between stressors, and the subsequent responses cannot be inferred. Accordingly, there may be confounding variables that we did not control for, such as traumatic experiences after military deployment. Of note, the R² estimates in some of the regression equations are relatively small, suggesting that there may be unknown variables (e.g., personality, resilience, social support, or post-deployment stressors), which might explain additional variance in post-deployment outcomes. Despite this, significant associations with a lower R² in a large sample such as in Studies 1 and 2 can indicate reliable findings, particularly when studying psychological phenomena in large samples (Figueiredo Filho et al., 2011).

In both studies, the respondents could reply either by mail or online. Differences in response modality may have affected our data. However, studies have shown that the response modality likely does not critically influence survey data (Gosling et al., 2004). In addition, the large size of both samples did not allow for collection of extensive anamnestic data or to conduct diagnostic interviews. The presented findings are based on short-form self-report measures and are subject to the limitations of the participants’ ability to self-evaluate adequately and retroactively.

Although the non-responder analysis revealed some response bias, the overall response rate was high in both studies, and the effect size estimates associated with the observed response bias were small. In addition, the strength of our conclusions regarding the impact of context and role on the association between KIC and post-deployment outcomes should be tempered by the observational designs employed by both studies, as well as any other factors that may vary systematically across samples. Regarding the latter, we did not directly measure expectations of combat or soldier mind-set in either study, their subjective experiences of expectancy violation in the face of exposure to war-zone stressors, or their spiritual/existential experience of KIC as a PMIE. This could be important, as both current diagnostic nosology (i.e., PTSD) and the MI construct may be insufficient to fully capture the psychological significance and meaning of KIC for individual veterans. In addition, the exact nature of various mission-specific activities is unknown. Finally, cultural norms in Norway discourage researchers from asking respondents about race or ethnicity (Kyllingstad, 2017). Accordingly, we do not have data on these variables.

Future Directions

The current findings on the diverging effects of KIC on veterans who served in peacekeeping versus combat-oriented missions have implications for the study of MI and the impact war-zone stressors have more broadly. While we infer that soldiers in a combat environment were less likely to experience KIC as a PMIE than soldiers in peacekeeping environment, further research is needed to confirm or refute this inference. However, it should be noted that when identifying potential PMIEs in war zones, research can easily be biased by common societal moral perceptions. In trying to study and categorize PMIEs, such social normative influences will have to be accounted for. Moreover, attempting to classify and investigate the moderating influence of known individual and contextual factors such as ROEs, training level, and military occupational specialty (MOS) is warranted. Future studies that explicitly integrate veterans’ assessment of beliefs about KIC (e.g., Killing Cognition Scale; Burkman et al., 2022) may be particularly fruitful. In addition, it may be that guilt and shame related to killing during deployment are mediated by the reactions and attitudes of civilians as veterans attempt to reintegrate into civilian life (Porter, 2018). While perhaps difficult to capture fully on a survey, the topic of other people’s reactions to having killed in combat would be well suited for qualitative study approaches. Finally, future research utilizing prospective designs may provide insights on how the psychological impact of KIC unfolds over time, which can lead to the development of strategies for prevention and mitigation of potential psychological distress associated with these experiences. Such effort could further expand on the current work by also exploring demographic variables not analyzed in the present study (e.g., gender, race/ethnicity).

Conclusion

In summary, the current study indicates that the impact of KIC on long-term psychological health is likely impacted by the context(s) in which the killing occurs. Moreover, there is likely a complex interplay between factors such as group norms, mission statements, pre-deployment expectations, and the process of reintegration into civilian society, affecting the psychological impact of KIC. This implies that setting clear expectations, for example, via ROEs, pre-deployment briefings, tactical training, mission statements, as well as providing psychological support informed by knowledge on the topic of MI, may help reduce potential post-deployment psychological distress associated with KIC. Given that veterans are not routinely assessed for killing experiences and may be hesitant to discuss KIC in clinical settings (Burkman et al., 2022; Darnell et al., 2022), results from the current study highlight the importance of attending to the context in which KIC occurs when addressing the topic during treatment.

Footnotes

Data Availability Statement

The data that support the findings of this study are available from the Norwegian Armed Forces Health Registry. Restrictions apply to the availability of these data, which were used under license for this study. Data are available upon request and subsequent permission from the Norwegian Armed Forces Health Registry.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Original data collection for both studies was funded by the Norwegian Department of Defense; however, data extractions were archival and, hence, not funded.

ORCID iD

Andreas Espetvedt Nordstrand

Author Biographies

Andreas Espetvedt Nordstrand: Commander Andreas Espetvedt Nordstrand, PhD, is a clinical psychologist and specialist in psychotherapy for trauma-related mental health disorders. Nordstrand is the head of research and development at the Norwegian Armed Force’s (NAF) Institute for Military Psychiatry. He is also an associate professor at the Norwegian University of Science and Technology (NTNU) and an affiliate professor at Northern Arizona University (NAU).

Laura K. Noll: Laura K. Noll, PhD, is a trauma psychologist working at the intersection of developmental psychology and prevention science to advance our understanding of psychosocial trauma across the lifespan. Through “rapid-cycle learning” in collaboration with community stakeholders, her research focuses on the development and implementation of innovative programs that foster resilience in underserved populations.

Ann Hergatt Huffman: Ann Huffman, PhD, is a professor of psychology and management at Northern Arizona University. Ann received her PhD in industrial-organizational psychology from Texas A&M University in 2004. Prior to Texas A&M University, Ann worked as a principal investigator with the Walter Reed Army Research Institute-Europe. Ann’s primary research interests include the work-life interface, high-stress occupations (e.g., police, military), and diversity in the workplace. Ann has published numerous research articles in journals such as the Academy of Management Journal and Human Resource Management and is the co-editor of the award-winning book, Green Organizations: Driving Change with IO Psychology.

Christer Lunde Gjerstad: Captain Christer Lunde Gjerstad is a clinical psychologist and researcher at the Institute of Military Psychiatry of the Norwegian Armed Forces Joint Medical Services, as well as a PhD student at the University of Oslo, Norway. His research primarily focuses on the mental health of military personnel, with interests including the application of emerging technologies, such as virtual reality, in the treatment of mental health problems.

Tore Tveitstul: Lieutenant Colonel Tore Tveitstul is a psychiatrist and currently working as a senior medical advisor within the Norwegian Armed Forces. Previously he commanded the Institute of Military Psychiatry—part of the Norwegian Armed Forces Joint Medical Services (NAFJMS). Tveitstul is one of two authors of the Emergency Psychiatric Handbook (written in Norwegian), used in civilian mental health care throughout Norway. He has experience from several military deployments.

Jon Gerhard Reichelt: Major general (R) Reichelt, MD, PhD, is a psychiatrist and served as the Surgeon General of the Joint Medical Forces of the Norwegian Armed Forces. Before taking on the leadership of the Joint Medical Services, he commanded the Institute of Military Psychiatry, where he also established a research and development unit focusing on military mental health. Reichelt has authored the much-endorsed book: Handbook in Military Psychiatry (Håndbok i Militærpsykiatri). Currently, Reichelt is a sought-after public speaker and contributor in various efforts to communicate popularized knowledge on mental health and resilience to a wider audience.

Lars-Petter Bakker: Major Lars-Petter Bakker, PhD, is currently working as a Liaison Officer for the Norwegian Armed Forces Joint Medical Services to the Norwegian Directorate of Health. Bakker is an officer and a clinical mental health nurse and former researcher at the Institute of Military Psychiatry of the Norwegian Armed Forces Joint Medical Services. Bakker has a PhD in health sciences. His research primarily focuses on the mental health of military personnel.

Leif Edward Ottesen Kennair: Leif Edward Ottesen Kennair, PhD, is a specialist in clinical adult psychology and a professor of personality psychology at the Norwegian University of Science and Technology (NTNU). He currently serves as the Editor-in-Chief of the Scandinavian Journal of Psychology. Previously, he was the Head of the Department of Psychology at NTNU. Kennair is an elected member of the Royal Norwegian Society of Sciences and Letters and was appointed to the Norwegian Cabinet Committee on Women’s Health. His research interests are diverse, focusing on the effective treatment of anxiety and depressive disorders, as well as evolutionary psychology. He applies Sexual Strategies Theory to explore topics such as jealousy, regret, sexual harassment, mate preferences, and the use of dating apps.

Ronny Helmersen Kristoffersen: Rear Admiral Lower Half (R) Kristoffersen is currently the chief of police in the district of Harstad, Kvaefjord, and Tjeldsund in northern Norway. Before retiring from the Norwegian Armed Forces (NAF), he had an extensive military career as a tactical operations officer and combat commander, serving in both the Army, Navy, and Air Force branches of the NAF. Notable commissions include Commanding Officer of the Coastal Ranger Command and Chief of the Situational and Operations Center in the Norwegian Intelligence Service. Kristoffersen has a master’s degree from the Naval Postgraduate School in defense analysis and special operations/irregular warfare. He has done several combat deployments to both Afghanistan and Syria. Kristoffersen is the recipient of the War Medal (for Valor) and the Purple Heart/Wounded in Combat Medal.

Hans Jakob Bøe: Major Hans Jakob Bøe is a clinical psychologist at the Institute of Military Psychiatry of the Norwegian Armed Forces Joint Medical Services and an assistant professor at the University of Oslo, Norway. His research interests are traumatic stress-related mental health, the mechanisms of psychological resilience, and the processes of personal growth after adverse experiences.

Robert E. Wickham: Robert Wickham works in the Department of Psychological Sciences at Northern Arizona University. Robert conducts research in personality psychology, quantitative psychology, and social psychology. His efforts are divided between basic research focusing on quantitative methodology, interpersonal processes, and psychological measurement, as well as the implementation and evaluation of programs related to housing, homelessness, community, and public health.

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